Bayesian Statistical Inference in Ion-Channel Models with Exact Missed Event Correction.

ABSTRACT: The stochastic behavior of single ion channels is most often described as an aggregated continuous-time Markov process with discrete states. For ligand-gated channels each state can represent a different conformation of the channel protein or a different number of bound ligands. Single-channel recordings show only whether the channel is open or shut: states of equal conductance are aggregated, so transitions between them have to be inferred indirectly. The requirement to filter noise from the raw signal further complicates the modeling process, as it limits the time resolution of the data. The consequence of the reduced bandwidth is that openings or shuttings that are shorter than the resolution cannot be observed; these are known as missed events. Postulated models fitted using filtered d

SUBMITTER: Epstein M 

PROVIDER: S-EPMC4968427 | biostudies-literature | 2016 Jul

REPOSITORIES: biostudies-literature